Some embodiments relate to vineyard agriculture. More precisely, some embodiments relate to an automatic tool for aiding the estimation of a harvest volume in a vine.
In order to best or better manage a vine, a winegrower must or should have an estimation of the volume of grape berry harvest. This estimation may in particular enable them to anticipate the human and hardware devices to be put in place in order to carry out the harvest efficiently, to optimize or enhance the organization of the harvest.
This estimation may be determined per plot of a vine, insofar as the conditions in respect of terroir, micro-climates, pruning and crop strategy, etc. may influence the evolution of the vine in a very local manner.
Furthermore, the evolution of this estimation may serve them as parameter to determine the best or better moment to carry out this harvest. It may also make it possible to detect anomalies of development of the grape berries.
In general, this knowledge is empirical or constructed manually. A wine-producer must or should therefore pass among the vines so as to determine a certain number of parameters, in particular the number of clusters per foot of vine and the mean weight of a cluster. In so far as it is humanly difficult to determine these measurements for the whole of a vine, a sampling must or should be performed. This sampling must or should be performed in as random a manner as possible and without human bias. The number of samples depends on the desired precision and on the variance within the geographical zone studied.
It follows therefrom that this scheme is complex to implement and also very time consuming. The error rate is furthermore fairly significant, generally between 20% and 50% and may attain 200% in certain cases. The article by P. Clingeleffer, G. Dunn, M. Krstic and S. Martin, “Crop development, crop estimation and crop control to secure quality and production of major wine grape varieties: A national approach”, in Technical Report, Grape and Wine Research and Development Corporation, Australia, 2001, may be consulted in this regard.
Furthermore, in order to obtain a satisfactory estimation, it is apparent that several samplings per season may be desired in this embodiment. This results in the destruction of an appreciable number of berries.
Moreover, automatic schemes have been contemplated for improving the process of estimating a harvest volume.
For example, the article “Yield Estimation in Vineyards: Experiments with Different Varietals and Calibration Procedure” by Stephen Nuske et al. in “Proceedings of Intelligent Robots and Systems (IROS)”, 2011 IEEE/RSJ International Conference 25-30 Sep. 2011, describes such a method.
The yield of the harvest is estimated on the basis of the number of berries counted automatically by the vehicle and by comparing this number with data from the previous year.